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Diversity

Diversity in data sampling is crucial across various use cases, including search, recommendation systems, and more. Ensuring diverse samples means capturing a wide range of variations and perspectives, which leads to more robust, unbiased, and comprehensive models. In search use cases, for instance, diversity helps avoid redundancy, ensuring that users are exposed to a broader set of relevant information rather than repeated similar results.

Papers

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Showing 7251–7300 of 9051 papers

TitleStatusHype
Sampling Strategies for GAN Synthetic Data—0
Sampling the "Inverse Set" of a Neuron: An Approach to Understanding Neural Nets—0
Efficient and Training-Free Control of Language Generation—0
Samsung Poland NLP Team at SemEval-2016 Task 1: Necessity for diversity; combining recursive autoencoders, WordNet and ensemble methods to measure semantic similarity.—0
SANE: Specialization-Aware Neural Network Ensemble—0
SAOR: Single-View Articulated Object Reconstruction—0
Sarcasm in Sight and Sound: Benchmarking and Expansion to Improve Multimodal Sarcasm Detection—0
Sat2Sound: A Unified Framework for Zero-Shot Soundscape Mapping—0
SATIN: A Multi-Task Metadataset for Classifying Satellite Imagery using Vision-Language Models—0
SatSynth: Augmenting Image-Mask Pairs through Diffusion Models for Aerial Semantic Segmentation—0
An Active Learning Framework for Inclusive Generation by Large Language Models—0
Says Who ? Identification of Expert versus Layman Critics' Reviews of Documentary Films—0
Scaffold-Based Multi-Objective Drug Candidate Optimization—0
An Active Learning Based Approach For Effective Video Annotation And Retrieval—0
An Abstraction Model for Semantic Segmentation Algorithms—0
Scalable and Ethical Insider Threat Detection through Data Synthesis and Analysis by LLMs—0
A Multi-View Discriminant Learning Approach for Indoor Localization Using Bimodal Features of CSI—0
Scalable Source Code Similarity Detection in Large Code Repositories—0
Scalable Surface Reconstruction from Point Clouds with Extreme Scale and Density Diversity—0
Scale-Aware Network with Regional and Semantic Attentions for Crowd Counting under Cluttered Background—0
Scaled ReLU Matters for Training Vision Transformers—0
A multi-platform metabolomics approach identifies novel biomarkers associated with bacterial diversity in the human vagina—0
A Multi-Persona Chatbot for Hotline Counselor Training—0
ScalingFilter: Assessing Data Quality through Inverse Utilization of Scaling Laws—0
A Comprehensive Social Bias Audit of Contrastive Vision Language Models—0
Scaling Language Data Import/Export with a Data Transformer Interface—0
A Multimodal Recaptioning Framework to Account for Perceptual Diversity in Multilingual Vision-Language Modeling—0
A multimodal gesture recognition dataset for desktop human-computer interaction—0
ScalingNoise: Scaling Inference-Time Search for Generating Infinite Videos—0
Scaling Parameter-Constrained Language Models with Quality Data—0
Scaling Policy Gradient Quality-Diversity with Massive Parallelization via Behavioral Variations—0
Scaling Pre-training to One Hundred Billion Data for Vision Language Models—0
Scaling Robot Policy Learning via Zero-Shot Labeling with Foundation Models—0
Scaling Robot Supervision to Hundreds of Hours with RoboTurk: Robotic Manipulation Dataset through Human Reasoning and Dexterity—0
A Multimodal Approach for Advanced Pest Detection and Classification—0
Scaling up Image Segmentation across Data and Tasks—0
A Multilingual BPE Embedding Space for Universal Sentiment Lexicon Induction—0
A multilayer PPI network analysis of different life stages in C. elegans—0
Scanpath Prediction in Panoramic Videos via Expected Code Length Minimization—0
Scattered Forest Search: Smarter Code Space Exploration with LLMs—0
Using LLMs as prompt modifier to avoid biases in AI image generators—0
SceneGen: Learning to Generate Realistic Traffic Scenes—0
Efficient Data Representation for Motion Forecasting: A Scene-Specific Trajectory Set Approach—0
Scene Summarization: Clustering Scene Videos into Spatially Diverse Frames—0
Using LSTMs for climate change assessment studies on droughts and floods—0
Layout Agnostic Scene Text Image Synthesis with Diffusion Models—0
Wills Aligner: Multi-Subject Collaborative Brain Visual Decoding—0
SceneX: Procedural Controllable Large-scale Scene Generation—0
Scheduling for Cellular Federated Edge Learning with Importance and Channel Awareness—0
Why scholars are diagramming neural network models—0
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